Evaluation of Single and Joint Toxicity of Perfluorinated Carboxylic Acids and Copper to Metal-Resistant Arthrobacter Strains

Advancing toxicity studies of per- and poly-fluoroalkyl substances (pfass) through machine learning: Models, mechanisms, and future directions

Perfluorinated and perfluoroalkyl substances (PFASs), encompassing a vast array of isomeric chemicals, are recognized as typical emerging contaminants with direct or potential impacts on human health and the ecological environment. With the complex and elusive toxicological profiles of PFASs, machine learning (ML) has been increasingly employed in their toxicity studies due to its proficiency in prediction and data analytics. This integration is poised to become a predominant trend in environmental toxicology, propelled by the swift advancements in computational technology. This review diligently examines the literature to encapsulate the varied objectives of employing ML in the toxicity studies of PFASs: (1) Utilizing ML to establish Quantitative Structure-Activity Relationship (QSAR) models for PFASs with diverse toxicity endpoints, facilitating the targeted toxicity prediction of unidentified PFASs; (2) Investigating and substantiating the Adverse Outcome Pathway (AOP) through the synergy of ML and traditional toxicological methods, with this refining the toxicity assessment framework for PFASs; (3) Dissecting and elucidating the features of established ML models to advance Open Research into the toxicity of PFASs, with a primary focus on determinants and mechanisms. The discourse extends to an in-depth examination of ML studies, segregating findings based on their distinct application trajectories. Given that ML represents a nascent paradigm within PFASs research, this review delineates the collective challenges encountered in the ML-mediated study of PFAS toxicity and proffers strategic guidance for ensuing investigations.

Transport and environmental risks of perfluoroalkyl acids in a large irrigation and drainage system for agricultural production

The quality of irrigation water and drainage water is essential for local ecosystem and human health in agricultural regions. In this study, the transport analysis, source identification, and environmental risk assessment of perfluoroalkyl acids (PFAAs) were conducted in the largest irrigation area in northern China. The concentrations of the total PFAAs (ΣPFAA) ranged from 41.5 to 263 ng/L in surface water, and the short-chain perfluoroalkyl carboxylic acids (PFCAs) and perfluorooctanoic acid (PFOA), were dominant with a total contribution of 94%. Generally, the ΣPFAA levels increased from irrigation waters to drainage and receiving lake waters. PFOA showed the highest increase, with potential emission sources located in the catchment of the sub main drainage ditch D5. More PFOA (36.8 kg/y) was outflowed from Ulansuhai Lake to the Yellow River than that inflowed from the Yellow River to the irrigation district (6.15 kg/y). The results of a risk assessment indicated that avian wildlife living in Ulansuhai Lake were threatened by the PFOA and perfluorobutane sulfonate (PFBS) pollution. The estimated daily intakes (EDIs) of the sum of the PFOA, perfluorononanoic acid (PFNA), perfluorohexane sulfonic acid (PFHxS), and perfluorooctane sulfonic acid (PFOS) through aquatic food consumption for people with the different aquatic food preferences accounted for 6-42% (urban) and 4-27% (rural) of the strictest tolerant daily intake (TDI) value. The results of this study highlight the impact of local emissions of PFAS on massive irrigation and drainage systems, and ultimately, the ecosystem and human health.

Formation of perfluorocarboxylic acids from 6:2 fluorotelomer sulfonate (6:2 FTS) in landfill leachate: Role of microbial communities

Fluorotelomer compounds in landfill leachate can undergo biotransformation under aerobic conditions and act as a secondary source of perfluorocarboxylic acids (PFCAs) to the environment. Very little is known about the role of various microbial communities towards fluorotelomer compounds biotransformation. Using an inoculum prepared from the sediment of a leachate collection ditch, 6:2 fluorotelomer sulfonate (6:2 FTS) biotransformation experiments were carried out. Specific substrates (i.e., glucose, ammonia) and ammonia-oxidizing inhibitor (allylthiourea) were used to produce two experimental runs with heterotrophic (HET) growth only and heterotrophic with ammonia-oxidizing and nitrite- oxidizing bacteria (HET + AOB + NOB). After 10 days, ∼20% of the spiked 6:2 FTS removal was observed in HET + AOB + NOB, compared to ∼7% under HET condition. Higher 6:2 FTS removal in HET + AOB + NOB likely resulted from ammonia monooxygenase enzyme that catalyzes the first step of ammonia oxidation. The HET + AOB + NOB condition also showed higher PFCA (C4-C6) formation (∼2% of initially spiked 6:2 FTS), possibly due to higher overall bioactivity. Microbial community analysis through 16s rRNA sequencing confirmed that Proteobacteria and Bacteroidetes were the most abundant phyla (>75% relative abundance) under all experimental conditions. High abundance of Actinobacteria (>17%) was observed under the HET + AOB + NOB condition on day 7. Since Actinobacteria can synthesize a wide range of enzymes including monooxygenases, they likely play an important role in 6:2 FTS biotransformation and PFCA production.